Semnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Integration of Artificial Neural Network and Taguchi Method for Prediction and Minimisation of Thick-Walled Polypropylene Gear Shrinkage249260893510.22075/macs.2024.33801.1646ENBikram SinghSolankiDepartment of Mechanical Engineering, PDPM Indian Institute of Information Technology Design & manufacturing Jabalpur Dumna Airport Road, Dumna – 482005, IndiaDevi SinghRawatDepartment of Mechanical Engineering, PDPM Indian Institute of Information Technology Design & manufacturing Jabalpur Dumna Airport Road, Dumna – 482005, IndiaHarpreetSinghDepartment of Mechanical Engineering, Dr B R Ambedkar National Institute of Technology Jalandhar– 144008, IndiaTanujaSheoreyDepartment of Mechanical Engineering, PDPM Indian Institute of Information Technology Design & manufacturing Jabalpur Dumna Airport Road, Dumna – 482005, IndiaJournal Article20240415The main aim of this research is to optimize the injection molding process parameters in order to mitigate the shrinkage of polypropylene (PP) spur gears. The methodology used integrated experimental approaches with artificial neural networks (ANN), and Taguchi methods to determine the optimal combination of injection molding parameters. The experimental data was used to create an ANN model using Matlab software that accurately predicts unseen data with a variation of less than 5%. The trained ANN model was further used to predict gear shrinkage in the context of Taguchi-based design of experiments. The investigation involved the use of Taguchi and analysis of variance techniques, determining that cooling time is the most important and relevant parameter. This is followed by packing time and melt temperature. The analysis revealed that the gears saw the least amount of shrinkage when the molding was carried out using the optimal combination of injection molding parameters.https://macs.semnan.ac.ir/article_8935_86230cc0bbf71c40b3c46f0f075349b2.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801A Comparative Study of Machine Learning Techniques for Predicting Mechanical Properties of Fused Deposition Modelling (FDM)-Based 3D-Printed Wood/PLA Biocomposite261270892610.22075/macs.2024.33776.1638ENPrashantAneraoDepartment of Mechanical Engineering, Vishwakarma Institute of Information Technology, Pune 411048, IndiaAtulKulkarniDepartment of Mechanical Engineering, Vishwakarma Institute of Information Technology, Pune 411048, IndiaYashwantMundeDepartment of Mechanical Engineering, Cummins College of Engineering for Women, Pune 411052, IndiaNamrateKharateDepartment of Computer Engineering, Vishwakarma Institute of Information Technology, Pune 411048, IndiaJournal Article20240413Wood/PLA biocomposite filament is a 3D printing material that blends Polylactic Acid (PLA), a biopolymer, with wood powder acting as reinforcement. This combination results in a sustainable 3D printing filament that has grown in popularity in recent years due to its eco-friendliness and the natural appearance of 3D-printed parts. To assess the suitability of wood/PLA biocomposite for various additive manufacturing applications, it is essential to determine its mechanical properties. This study employs fused deposition modeling (FDM) as the additive manufacturing process and focuses on assessing the mechanical properties (tensile, flexural, and impact) of 3D-printed biocomposite. The Taguchi L27 design of the experiments is utilized, and the key process parameters under consideration are infill pattern, layer thickness, raster angle, nozzle temperature, and infill density. A layer thickness of 0.3 mm and an infill density of 100% yielded the highest tensile strength of 42.46 MPa, flexural strength of 83.43 MPa, and impact strength of 44.76 J/m. The dataset has been carefully prepared to facilitate machine learning for both training and testing, and it contains the experimental results and associated process parameters. Four distinct machine learning algorithms have been selected for predictive modeling: Linear Regression, Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Adaptive Boosting (AdaBoost). Given the intricate nature of the dataset and the presence of nonlinear relationships between parameters, XGBoost and AdaBoost exhibited exceptional performance. Notably, the XGBoost model delivered the most accurate predictions. The results were assessed using the coefficient of determination (R2), and the achieved values for all observed mechanical properties were found to be greater than 0.99. The results signify the remarkable predictive capabilities of the machine learning model. This study provides valuable insights into using machine learning to predict the mechanical properties of 3D-printed wood/PLA composites, supporting progress in sustainable materials engineering and additive manufacturing.https://macs.semnan.ac.ir/article_8926_953ab3325e328f1f092228dc6085b441.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Mechanical Properties of Hemp Fiber-Reinforced Polypropylene Composites for Drone Propeller Guard Application271277893710.22075/macs.2024.33806.1647ENWitawatSingsangDepartment of Production Engineering and Quality Management, Faculty of Industrial Technology, Rambhai Barni Rajabhat University, Chanthaburi, 22000, ThailandThanasakKhamsinDepartment of Aircraft Parts Manufacturing Technology, Faculty of Industrial Technology, Rambhai Barni Rajabhat University, Chanthaburi, 22000, ThailandChayapolPrachumchonDepartment of Aircraft Parts Manufacturing Technology, Faculty of Industrial Technology, Rambhai Barni Rajabhat University, Chanthaburi, 22000, ThailandAnurakRodbumrungDepartment of Production Engineering and Quality Management, Faculty of Industrial Technology, Rambhai Barni Rajabhat University, Chanthaburi, 22000, ThailandBenjamasNetiworaruksaDepartment of Production Engineering and Quality Management, Faculty of Industrial Technology, Rambhai Barni Rajabhat University,
Chanthaburi, 22000, ThailandNatkritaPrasoetsophaDepartment of Materials Engineering, Faculty of Engineering and Technology, Rajamangala University of Technology Isan, Nakhon Ratchasima, 30000, ThailandIng-ornSittitanadolDepartment of Metallurgical Engineering, Faculty of Engineering, Rajamangala University of Technology Isan, Khon Kaen Campus, Khon Kaen, 40000, ThailandJournal Article20240415A propeller guard is an instrument that helps to avoid Unmanned Aerial Vehicles (UAVs) or drone damage. Commercially, they are made from an engineering plastic such as Acrylonitrile Butadiene Styrene (ABS). This work aims to introduce the hemp fiber-reinforced polypropylene composites as a new competitive material for propeller guards. In this study, polypropylene was thermally mixed with different ratios of hemp fibers by internal mixing at 190°C. Tensile and impact testing were carried out according to ASTM D638 and ASTM D256, respectively. The results showed that the high contents of hemp fibers can enhance the modulus of their composites. Polypropylene composite with 45 wt.% of hemp fibers obtained the highest modulus at 1169.4 MPa. Also, the impact resistances of these composites were higher while the fiber contents were increased. Furthermore, application in drone propeller guard was executed by SIMCENTER 3D software for proving their propeller protection performance of as-prepared composites. The results indicated that polypropylene and its hemp fibers-reinforced composites could be the materials for this drone propeller guard.https://macs.semnan.ac.ir/article_8937_88bd75a393d724934091fab4cc2c6c8e.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Enhancement of Compressive Strength in Cement Admixed Bangkok Clay with Glass Fiber and Bottom Ash for Eco-Friendly Functional Road Materials279292892910.22075/macs.2024.33848.1653ENSakolPochalardDoctor of Engineering Program in Construction Engineering Technology, Graduate College, King Mongkut’s University of Technology North Bangkok, Bangkok, ThailandBuilding and Landscape Division, Suan Dusit University, Bangkok, ThailandChalermponWungsumpowDoctor of Engineering Program in Construction Engineering Technology, Graduate College, King Mongkut’s University of Technology North Bangkok, Bangkok, ThailandOperations Center of Integrated Innovation Research and Development under Industrial Standards, KMUTNB Techno Park, King Mongkut's University of Technology North Bangkok, Bangkok, ThailandKeeratikanPiriyakulDepartment of Civil and Environmental Engineering Technology, College of Industrial Technology, King Mongkut’s University of Technology North Bangkok, Bangkok, ThailandJournal Article20240420This article aims at the development of new eco-friendly functional road materials, examining the optimum mixing ratio of cement, bottom ash, glass fibers, and the mechanical properties of soil-cement subbase (pavement) materials. The optimum ratio of cement, bottom ash, and glass fibers was determined for the mixing of soil-cement as eco-friendly functional road materials. This study was carried out by using the unconfined compression test. All soil-cement samples were mixed at the liquid limit of 88%, with varying glass fiber content between 0.5, 1.0, 1.5, 2.0, and 2.5% by volume respectively. The glass fiber lengths were used 3, 6, and 12 mm. The OPC content was added between 2, 4, 6, 8, and 10%, respectively by dry weight. The bottom ash content was 5, 10, 15, 20, 25 and 30% by volume respectively. All soil-cement samples were cured for 7, 14, 28, 60 and 90 days. It was found that the optimum OPC soil-cement content mixture was around 8-10% according to ACI 230.1R-09 standard which requires OPC of 10-16% and the optimum fiber content was between 1.0 and 1.5%. The best UCS result for glass fiber length was 12mm. Finally, the optimum bottom ash content was 5-10%, and the recommended curing period should exceed 28-90 days.https://macs.semnan.ac.ir/article_8929_117de98af772c81cc42aaa3f228da251.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20240801Design and Development of a Pine Needle Briquetting Machine for the Uttarakhand Region of India293303892710.22075/macs.2024.33800.1644ENTejas PramodNaikDepartment of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee - 247667, Uttarakhand, IndiaCommonwealth Scholar, Department of Mechanical Engineering, University of Bath, Bath - BA2 7AY, England, United KingdomDesign Innovation Centre, Indian Institute of Technology Roorkee, Roorkee - 247667, Uttarakhand, IndiaSoumyajeetJaiswalDepartment of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee - 247667, Uttarakhand, IndiaIndian Institute of Management Bangalore, Bengaluru - 560076, Karnataka, IndiaInderdeepSinghDepartment of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee - 247667, Uttarakhand, IndiaDesign Innovation Centre, Indian Institute of Technology Roorkee, Roorkee - 247667, Uttarakhand, IndiaApurbba KumarSharmaDepartment of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee - 247667, Uttarakhand, IndiaDesign Innovation Centre, Indian Institute of Technology Roorkee, Roorkee - 247667, Uttarakhand, IndiaAyushJoshiArya Vihar Ashram, Sri Arya Trust, Uttarkashi - 249194, Uttarakhand, IndiaJournal Article20240415Fossil fuels, a non-renewable source, supply more than 81% of the world’s primary energy and contribute heavily to global climate change. This paper represents a strategy to address the administration of forest bio residue in the northern Himalayan district of India. Uttarakhand state, the north part of India, is rich in bio residues such as Pine needles of Chir Pine (Pinus roxburghii). Every year during the summer, there is a forest fire breakout, mainly caused by these dry pine needles, which cover a forest floor and are highly flammable. This forest bio residue is renewable and is a potential energy source for rural livelihoods, which would also generate social business enterprises among the locals. This is an effort to develop a practical manual-operated briquetting machine (BM) capable of fabricating briquettes from forest waste. The primary materials utilized to make briquettes are pine needles and forest waste. The proposed method inculcates principles of compression molding along with necessary optimizations. Briquetting is one of the cheapest ways to harvest the destructive energy of pine needles in a clean and economically viable way. Briquetting machines reduce forest fires by reducing dependency on wood from forests for fuel while simultaneously lowering carbon emissions by using biomass or agricultural waste as alternative fuel sources. This dual benefit protects forests and helps battle climate change and local air pollution, making it a long-term option for environmental protection. The developed BM is one solution that can solve the dual purpose of climate change mitigation and employment. The designed and developed machine fabricates thirty-three briquettes per hour and is currently installed in the Uttarkashi district of Uttarakhand, India.https://macs.semnan.ac.ir/article_8927_15b963c5f70b6593507e1ccb81ffc7c4.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Exploring Multi-Scale Thermal Behaviour in Pin-on-Disc Systems for Organic, Metallic, Ceramic, and Polymer Composites305317900710.22075/macs.2024.33789.1640ENHemantNagoriyaDepartment of Mechanical Engineering, UIE, Chandigarh University, Gharuan, Mohali, Punjab, 140413, IndiaGauravAroraDepartment of Mechanical Engineering, UIE, Chandigarh University, Gharuan, Mohali, Punjab, 140413, IndiaJournal Article20240414This paper presents a multi-scale strategy for the thermal simulation of frictional systems, such as brakes, considering the microscale properties of the polymer composites. A finite element model is supposed to model the system components at the macro scale. At the microscale, the thermal properties are evaluated to identify the effective thermal properties of the polymer composites. As regards wear, Archard's law is used with a wear rate coefficient depending on temperature. The micro-scale properties of the polymer composites are integrated into the macro-scale model using the COMSOL computational package. In the conducted study, it is determined that the contact temperature for organic disk brake pad material reaches the highest value at 727 K, followed by ceramic material pad at 691 K, and semi-metallic material at 689 K. Focusing on epoxy and epoxy-fiber composites, it is observed that the Kevlar-epoxy composite exhibits temperature performance characteristics comparable to those of the semi-metallic and ceramic materials, registering a contact temperature of 693 K. In contrast, both epoxy and epoxy-carbon fiber composites display significantly higher temperatures, with values of 1254 K and 944 K, respectively. Consequently, these findings suggest that Kevlar epoxy shows promise in serving as a future brake pad material for the automotive industry. The multi-scale study on different materials focusing on the use of computational results for replacing the traditional brake pad material with advanced composites is the novelty of the study.https://macs.semnan.ac.ir/article_9007_73d80c93adb141fe50370329bc834d48.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Effect of ON and OFF Axis Open Hole Tensile Testing of GFRP/Epoxy Composites319328893110.22075/macs.2024.33793.1645ENSunithBabu LoganathanDepartment of Mechanical Engineering, Ramaiah Institute of Technology, Bengaluru, 560054, IndiaCentre for Advanced Materials Technology, Ramaiah Institute of Technology, Bengaluru, 560054, IndiaAshokKumar KrishnappaDepartment of Mechanical Engineering, Ramaiah Institute of Technology, Bengaluru, 560054, IndiaJayaChristiyan Kumaravelu Grace Jesu BaiDepartment of Mechanical Engineering, Ramaiah Institute of Technology, Bengaluru, 560054, IndiaRitinPaviralaDepartment of Mechanical Engineering, Ramaiah Institute of Technology, Bengaluru, 560054, IndiaRajeshMathivananDepartment of Mechanical Engineering, PES University, Bengaluru, 560085, IndiaJournal Article20240415Composites are widely used for different applications in engineering mainly due to their tailored benefits, durability, reduced maintenance, and enhanced performance. GFRP is a synthetic material that has revolutionized the aerospace industry, offering a high strength-to-weight ratio, fuel efficiency, and enhanced performance for advanced applications. In structures like aircraft components, holes or notches are often present due to design requirements or secondary joining processes through rivets or bolted connections, which leads to wear and tear. Further, how these materials behave under tensile loads near these openings is critical for ensuring the safety and reliability of such structures. In the present study, GFRP/Epoxy composite laminates are subjected to open hole tensile test under ON and OFF axis orientations. The effect of loading under different sequences was studied. The nature of failure near the hole region was reviewed and presented. It is noted that the dominant failure was LGM type under the ON-axis and different under the OFF-axis which is not limited to shear failure, interlaminar delamination, and mixed mode failures. These trends are noted for different hole dia, namely 6,9,12 and 18mm. The study also presents the nature of the stress-strain curve for both configurations. The OFF-axis specimens displayed a non-linear behavior to failure as compared to the On-axis type. While, the on-axis specimens showed a marked reduction in peak load and tensile strength as hole dia increased with reductions up to 65.23% and 63.57%, respectively relative to hole-less specimens. The inclined failure in off-axis specimens varied between 500 - 550. Further, the damage tolerance in OFF-axis samples was higher as compared to ON-axis specimens.https://macs.semnan.ac.ir/article_8931_57548e4ee1fe1fc8608cd1dfb00c4c61.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Bearing Response Prediction in Hydrothermal Aged Carbon Fiber Reinforced Epoxy Composite Joints Using Machine Learning Techniques329338893610.22075/macs.2024.33802.1643ENMohitKumarDepartment of Mechanical Engineering, Chandigarh University, Mohali, Punjab, 140301, IndiaGovindVashishthaFaculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, 50-421 Wroclaw, PolandBabitaDhimanDepartment of Electronics and Communication Engineering, Chandigarh University, Mohali, Punjab, 140301, IndiaSumikaChauhanFaculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, 50-421 Wroclaw, PolandJournal Article20240414The work focuses on predicting the bearing response in hydrothermal-aged carbon fiber-reinforced epoxy composite (CFREC) joints through the utilization of machine learning techniques. CFREC are extensively employed in aerospace and other high-performance applications, and their long-term structural integrity is of paramount importance. The hydrothermal aging process can significantly affect the mechanical behavior of such composites, particularly in joint configurations. In this research, an innovative support vector regression approach is present that leverages machine learning algorithms to forecast the bearing response of CFREC joints after undergoing hydrothermal aging. The study encompasses the development of predictive models using a comprehensive dataset of experimental observations. The machine learning technique, support vector regression is trained and evaluated to assess their accuracy and reliability in predicting bearing response. The results show that the overall percent reduction in bearing response, after 30 days of pristine composite bolted joints at 0 Nm bolt torque shows reductions of 23.22 % at 65°C, respectively. Conversely, under the same conditions, MWCNTs added composite bolted joints exhibit only a 9.2% reduction. The predictive models find the value of 0.0081 RSME and 0.8 R2 respectively through support vector regression confirming that the predicted values lie in between the upper and lower bond.https://macs.semnan.ac.ir/article_8936_7040758119056bb44a15ac043fa994a4.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Complementary Split Ring Resonator-Inspired Antenna for Wearable Multiband Applications Using Biodegradable Polylactic Acid339352893810.22075/macs.2024.33850.1658ENSaranyaSrinivasanDepartment of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, 641202, IndiaHariharanSelvarajDepartment of Electronics and Communication Engineering, Sri Ramakrishna Engineering College, Coimbatore, 641022, IndiaGopiPitchaimaniDepartment of Electronics and Communication Engineering, Sri Ramakrishna Engineering College, Coimbatore, 641022, IndiaKamalBishnoiDepartment of Electronics and Communication Engineering, Sri Ramakrishna Engineering College, Coimbatore, 641022, IndiaJournal Article20240421In this manuscript, replacing traditional antennas with biodegradable PLA substrates aims to reduce e-waste in today's technologically advanced age. This work achieves its objectives by designing the miniaturized (56 x 56 x 1.6) mm3 hexagonal patch antenna with partial ground (18.2 x 52) mm2 and incorporating complementary split ring resonators (CSRRs) in the HFSS (High-Frequency Structure Simulator). This innovative approach combines unconventional antenna design with metamaterial technology to enhance antenna performance, making it flexible, lightweight, and suitable for multi-band applications. An evaluation of PLA compared to other substrates revealed that PLA is more suitable for its eco-friendliness, and the simulation result is also satisfactory for bandwidth, return loss, VSWR, directivity, efficiency, and other parameters. Additionally, the integration of taffeta fabric as a conductive patch material provided elasticity and enhanced wearability. Using this unique method, the proposed antenna resonates at multiband frequencies of 2.6 GHz, 8.6 GHz, 10.5 GHz, 12.4 GHz, and 15.3 GHz, which gives return losses of -26.84 dB, -22.16 dB, -29.87 dB, -39.43 dB, and -26.35 dB, respectively. In addition to its biocompatibility and achievement of the SAR threshold, the antenna serves as a long-term solution for multi-band wireless applications. This further advances the realm of environmentally friendly wearable technology.https://macs.semnan.ac.ir/article_8938_c7da5b38d5507db5da71491291cd67c8.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Artificial Neural Network (ANN) Approach to Predict Tensile Properties of Longitudinally Placed Fiber Reinforced Polymeric Composites including Interphase353360898010.22075/macs.2024.33874.1664ENSagarChokshiDepartment of Mechanical Engineering, Chandubhai S. Patel Institute of Technology, Charotar University of Science and Technology, Changa-388421, Gujarat, IndiaPiyushGohilDepartment of Mechanical Engineering, Faculty of Technology and Engineering, The Maharaja Sayajirao University of Baroda, Vadodara-390001, Gujarat, IndiaVijayParmarDepartment of Mechanical Engineering, Faculty of Technology and Engineering, The Maharaja Sayajirao University of Baroda, Vadodara-390001, Gujarat, IndiaVijaykumarChaudharyDepartment of Mechanical Engineering, Chandubhai S. Patel Institute of Technology, Charotar University of Science and Technology, Changa-388421, Gujarat, India0000-0001-9938-6844Journal Article20240423Machine Learning has become prevalent nowadays for predicting data on the mechanical properties of various materials and is widely used in various polymeric applications. In the present study, Artificial Neural Network (ANN), a computational tool is used to predict the elastic modulus of a composite of longitudinally placed fiber-reinforced polymeric composite. The novelty in carried work is that the property prediction is carried out considering interphase and its properties. For this, tensile properties data of Longitudinally Placed Bamboo Fiber Reinforced Polyester Composite (LUDBPC), Longitudinally Placed Flax Fiber Reinforced Polyester Composite (LUDFPC) and Longitudinally Placed Jute Fiber Reinforced Polyester Composite (LUDJPC) has been procured to generate ANN models. The Levenberg-Marquardt training algorithm is used to generate the ANN models as it gives more accurate results compared to other ANN algorithms based on interphase properties data. The validation of ANN models was also carried out based on fresh experimental results of BPC/FPC by doing the fabrication with hand layup technique and testing of composites with a Universal Testing Machine (UTM). The present work signifies that the developed ANN models give accurate results with experimental results for the prediction of elastic modulus of composite (Ecl) and it can be used for the prediction of longitudinally placed fiber-reinforced composite and Ecl of BPC at volume fraction of fiber (vf):22% is 2248.75 MPa and Ecl of FPC at vf:10% is 3210.50 MPa.https://macs.semnan.ac.ir/article_8980_187576ddf606902249196f9627a8584b.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801S-Parameter Analysis of Three-Layered Aperture Coupled Antenna with a Flame Retardant-4 Composite Material as Substrate for Biomedical Applications361369901210.22075/macs.2024.33838.1651ENG. S.DeepthyDepartment of ECE, Karunya Institute of Technology and Sciences, Karunya Nagar, Coimbatore, 641 114, Tamil Nadu, IndiaDepartment of ECE, Rajagiri School of Engineering and Technology, Rajagiri Valley, Kakkanad, Kochi, 682 039, Kerala, IndiaM.NesasudhaDepartment of ECE, Karunya Institute of Technology and Sciences, Karunya Nagar, Coimbatore, 641 114, Tamil Nadu, IndiaT. A.KarthikeyanDepartment of ECE, Karunya Institute of Technology and Sciences, Karunya Nagar, Coimbatore, 641 114, Tamil Nadu, IndiaJournal Article20240420In biomedical applications, particularly for tumor detection, the need for high-resolution imaging systems is critical. This paper presents the “S” parameter analysis of a three-layer stacked microstrip antenna with Defected Ground Structure (DGS) having a “+” shaped slot. The dimension of the antenna provides an enhanced performance ranging from 4.5-12 GHz. An aperture-coupled mechanism where a direct connection between feed and the FR-4 (Flame Retardant 4) substrate employing the need for three substrates having a dielectric constant (εr = 4.4) and having a thickness of 1.57mm each is utilized in this design. The composite material known as FR4 is structured with its fundamental layer consisting of fiberglass, woven into a thin, fabric-like sheet, providing essential structural support. This innermost layer of fiberglass imparts the necessary stability to FR4. It is then encased and secured by a flame-resistant epoxy resin. The antenna structure incorporates a parasitic patch as the topmost layer and an active patch that is placed below the substrate layer both of which incorporate slots for enhanced performance. The ground layer is sandwiched between the active layer and feedline which ensures separation between the two. Such a structure can help in optimizing both the radiating patch and the feedline independently. The performance of the designed antenna is studied for various slot configurations where the S- S-parameter analysis shows that the antenna provides wideband behavior which makes it suitable for biomedical applications like breast cancer detection. The S parameter analysis done in HFSS software shows a maximum return loss of -40dB which is performed for various slot configurations. The increasing demand for UWB communication systems underscores the critical importance of advanced antenna design to meet expanding data transmission requirements. The design of UWB antennas plays a crucial role in biomedical applications like breast cancer detection, where precise signal accuracy and penetration depth are essential for enhancing diagnostic efficacy and treatment monitoring.https://macs.semnan.ac.ir/article_9012_e026b0dcc3626a7c38d8e13cc1f24fdd.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Experimental Investigation of Repair of Glass Epoxy Composite with Edge and Center Crack by Epoxy Resin371377898210.22075/macs.2024.33897.1663ENThillaisekarSivagangaiSimcrash Center, Department of Aerospace Engineering, Hindustan Institute of Technology and Science, Chennai 603103, IndiaAlthafMohammad YounusDepartment of Aeronautical Engineering, Hindustan Institute of Technology and Science, Chennai 603103, IndiaJournal Article20240423The aerospace and automotive industries widely use composite materials due to their weight-to-strength ratios. One of the most significant problems with composites is repair and maintenance. This study attempts to repair glass epoxy composites. The repair process involves two stages: 1)optimization of the position of the hole and 2) repair work. To optimize the repair techniques, two distinct holes were performed: 1) at the center of the specimen and 2) at the edges of the specimen. As a result, the hole drilled at the center gives higher strength than the hole drilled at the edges. After the optimization, samples were repaired with a single hole in the center and peak loads of 60% and 90%. The cracked and delaminated areas were repaired with epoxy/hardener. The repaired samples were subjected to a three-point bending test, and the results were compared with the Neat GFRP samples. The results show that the curves of the repaired samples aligned with both the post and the residual flexural strength. The residual flexural strength of the 60% and 90% peak-loaded repaired samples retains about 47% and 76%, respectively.https://macs.semnan.ac.ir/article_8982_0b867566f93997d46845d8d45b69957b.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Mechanical Properties and Water Absorption of Epoxy Composites Reinforced with Treated Long Hair Fiber for Sustainable Manufacturing379392919010.22075/macs.2024.33759.1635ENDeepakKachhotDepartment of Mechanical Engineering, Amity University Rajasthan, IndiaRishiDewanganDepartment of Mechanical Engineering, Amity University Rajasthan, IndiaMotilalRinawaDepartment of Mechanical Engineering, Govt. Engineering College Jhalawar, Rajasthan, IndiaUmesh KumarDwivediAmity School of Applied Science, Amity University Rajasthan, IndiaJournal Article20240411This study focused on exploring the alternative fibers that not only serve as substitutes for synthetic ones, but also offer ease of availability, cost-effectiveness, biodegradability, and superior specific properties. Extensive research suggests natural fibers can meet these desired criteria when replacing synthetic fibers. Here pig hairs were examined as suitable reinforcement for epoxy polymer and investigated the mechanical properties and water absorption for sustainable manufacturing. Pig hair was treated with NaOH solution and incorporated into an epoxy resin matrix at varying weight percentages (10% to 40%). Experimental results showed that the composites having 30wt% fiber exhibit the highest tensile modulus which is 65% higher and flexural modulus which is 122% higher than the value of the control sample. As the fiber loading increases impact strength also increases which is found to be 7 times higher than the control sample for 40wt% fiber loading. The water absorption resulted that after 40 days, the 10 wt% pig hair fiber composites absorbed only 2.5% water, while the highest water absorption was 9.01% for the 40 wt% sample. SEM analysis confirms robust interfacial bonding between pig hair fibers and epoxy matrix, which suggests that the product of the composites may be suitable for automobile, marine, and shed manufacturing Industries.https://macs.semnan.ac.ir/article_9190_86129cd0ebdc8631fac340c24f9bb387.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801The Impact of Fiber Architecture on the Mechanical Properties of Hand Lay-up Reinforced Polyester Resin393400907010.22075/macs.2024.33840.1650ENWitawatSingsangDepartment of Production Engineering and Quality Management, Faculty of Industrial Technology, Rambhai Barni Rajabhat University, Chanthaburi, 22000, ThailandNatkritaPrasoetsophaDepartment of Materials Engineering, Faculty of Engineering and Technology, Rajamangala University of Technology Isan, Nakhon Ratchasima, 30000, ThailandTanakornLanwongDepartment of Metallurgical Engineering, Faculty of Engineering, Rajamangala University of Technology Isan, Khon Kaen Campus, Khon Kaen, 40000, ThailandNawapolKhumsamorDepartment of Metallurgical Engineering, Faculty of Engineering, Rajamangala University of Technology Isan, Khon Kaen Campus, Khon Kaen, 40000, ThailandPongsaphatNomraweeDepartment of Metallurgical Engineering, Faculty of Engineering, Rajamangala University of Technology Isan, Khon Kaen Campus, Khon Kaen, 40000, ThailandIng-ornSittitanadolDepartment of Metallurgical Engineering, Faculty of Engineering, Rajamangala University of Technology Isan, Khon Kaen Campus, Khon Kaen, 40000, ThailandJournal Article20240419This work aimed to improve the mechanical properties of a glass fiber-reinforced polyester resin composite material. The research evaluated the effect of glass fiber architecture on these properties by using fibrous-like and sheet-like glass fibers to reinforce polyester resins via a hand lay-up method. The prepared specimens were analyzed for various mechanical properties, including tensile, hardness, and flexural, according to ASTM standards. The results showed that glass fiber reinforcement in both fibrous-like and sheet-like forms enhanced the mechanical properties of polyester resin. Specifically, polyester resin composites reinforced with fibrous-like glass fibers exhibited superior mechanical properties. The hardness was 28.03±3.49 HV, the tensile strength was 76.31±11.38 MPa, the tensile modulus was 2293.92±116.68 MPa, and the percent elongation at break was 5.92%, with a flexural resistance of 114.49±22.21 MPa and a flexural modulus of 5377.37±596.62 MPa. Additionally, a simulation model using SIMCENTER 3D software was utilized to assess the stress application on a large water tank fabricated by the as-prepared composites. The simulation confirmed the performance of these composites.https://macs.semnan.ac.ir/article_9070_74cec2609b5a6cfaa42a5eda8862abdd.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Patch Antennas with PDMS Substrate to Detect Tumors and their Data Transmission through ERPO-OFDM Modulation Technique in VLC401411901310.22075/macs.2024.33847.1652ENKarthikeyanThavittupalayam AngappanaDepartment of ECE, Karunya Institute of Technology and Sciences, Coimbatore, 641114, IndiaNesasudhaMosesDepartment of ECE, Karunya Institute of Technology and Sciences, Coimbatore, 641114, IndiaAnithaVijayalakshmiDepartment of ECE, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, IndiaJournal Article20240420A Patch antenna is a kind of antenna with a low profile, which can be fixed on a surface. It communicates and gets electromagnetic waves inferred way. The boundaries of the antenna incorporate radiation design, gain, impedance, and frequency. Polydimethylsiloxane (PDMS) is utilized as a substrate in patch antennas. The existence of a tumor can be effectively recognized by the current density of the phantom. The difference in the current density value of phantom without tumor and with tumor shows the presence of the tumor. The first four antenna designs show a huge contrast in current density, the leftover two designs have little distinction of current density worth of phantoms. Six unique constructions of microstrip antenna are intended for skin tumor detection. In these six designs, the model for skin cancer recognition utilizing truncated corner, the working frequency is 2.492 GHz and S11 is –38 dB. The current density of the design relies on phantom characteristics. The acquired current density value of phantom without the growth of the tumor, with tumor, and with dangerous growth of the malignant tumor is (171.562, 193.381, and 204.199) A/m^2 and the Specific Absorption Rate (SAR) value is (1.14049, 1.27013 and 1.26088) W/Kg respectively. Visible Light Communication (VLC) system using Orthogonal Frequency Division Multiplexing (OFDM) supports high-speed transmission. The effectively-identified tumor can be communicated through gadgets using Enhanced Reverse Polarity Optical OFDM (ERPO-OFDM) technique. It’s a multicarrier modulation that supports information transmission through Light Emitting Diodes (LEDs).https://macs.semnan.ac.ir/article_9013_12c6a459eeecff541f29e6c6775e5060.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Stacking-Sequence Optimization and Buckling Analysis of Graphene/Fiber-Reinforced Laminated Plates413424948710.22075/macs.2025.34916.1706ENRanganai TawandaMoyoDepartment of Mechanical Engineering, Durban University of Technology, Durban, 4001, South AfricaPavel YaroslavovichTabakovDepartment of Mechanical Engineering and Institute for Systems Science, Durban University of Technology, Durban, 4001, South AfricaJournal Article20240731The use of graphene-based composites, particularly in aerospace and structural applications, has received extensive attention in recent years. Graphene nanoplatelets are normally used to enhance composite materials' mechanical, thermal, and electrical properties. The present research investigates the biaxial buckling of two- and three-phase angle ply laminated plates reinforced with carbon or glass fibers. The simply supported plate in this study is defined as a 16-ply symmetric and balanced laminate with uniform distribution of the fiber and graphene content through the thickness. The objective of this work is to produce a cost-effective design using the minimum amount of expensive reinforcement while maximizing the compressive buckling load. The desired results are achieved by finding the optimal stacking sequence of reinforcement fibers, as well as selecting an optimal amount of graphene nanoplatelets and fiber volume content. Numerical results are first obtained for two-phase laminates with different ratios of applied loads. Further, three-phase laminates are studied and, among other things, the relationship between the fiber and graphene content is analyzed. The optimization procedures were performed by particle swarm optimization (PSO) for continuous optimization and genetic algorithm (GA) for integer optimization. The software applications were written by the authors and proved to be very fast and efficient.https://macs.semnan.ac.ir/article_9487_94eff08c8c4436f83a6d8555d72a705d.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Quantum Machine Learning Approach for the Prediction of Surface Roughness in Additive Manufactured Specimens425433900810.22075/macs.2024.33798.1642ENAkshanshMishraSchool of Industrial and Information Engineering, Politecnico Di Milano, Milan, Italy0000-0003-4939-359XVijaykumar ShivashankarJattiSymbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, Maharashtra, IndiaJournal Article20240414One of the most important factors affecting the functioning and performance of additively produced components is surface roughness. Precise estimation of surface roughness is essential for streamlining production procedures and guaranteeing product quality. Recently, quantum computing has drawn interest as a possible way to solve challenging issues and produce accurate prediction models. For the first time, we compare three quantum algorithms in-depth in this research paper for surface roughness prediction in additively manufactured specimens: the Quantum Neural Network (QNN), Quantum Forest (Q-Forest), and Variational Quantum Classifier (VQC) modified for regression. Mean Squared Error (MSE), Mean Absolute Error (MAE), and Explained Variance Score (EVS) are the assessment metrics we use to evaluate the algorithms' performance. With an MSE of 56.905, an MAE of 7.479, and an EVS of 0.2957, the Q-Forest algorithm outperforms the other algorithms, according to our data. On the other hand, the QNN method shows a negative EVS of -0.444 along with a higher MSE of 60.840 and MAE of 7.671, suggesting that it might not be the best choice for surface roughness prediction in this application. The regression-adapted VQC has an MSE of 59.121, an MAE of 7.597, and an EVS of -0.0106, indicating that it performs inferior to the Q-Forest approach as well.https://macs.semnan.ac.ir/article_9008_9c59cb292ac7e52f2b71300e390cd53b.pdfSemnan University PressMechanics of Advanced Composite Structures2423-482612Special Issue 2: Mechanics of Advanced Fiber-Reinforced Composite Structures20250801Achieving High Strength in Fe-Based Metallic Glass Reinforced Aluminum Matrix Composites through Combined Ball Milling and Spark Plasma Sintering435446963510.22075/macs.2025.33187.1612ENMohammad RezaRezaeiSchool of Engineering, Damghan University, Damghan, 36716-45667, IranRezaNazemnezhadSchool of Engineering, Damghan University, Damghan, 36716-45667, IranErfanKhanmohammadiSchool of Engineering, Damghan University, Damghan, 36716-45667, IranJournal Article20240204This study examines the production and analysis of aluminum matrix composites reinforced with Fe-based metallic glass (FMG) using powder metallurgy techniques. FMG particles with nominal composition Fe75Si15B5Zr5 were synthesized using the mechanical alloying process. For the fabrication of composites, two methods were used: (a) mixing gas atomized pure aluminum (GA) powder with FMG powder and consolidating via spark plasma sintering (SPS) to form the GA/FMG composite, and (b) ball milling the GA powder before mixing with FMG powder and SPS consolidation to produce the (GA+BM)/FMG composite. As a control, pure aluminum powders before and after the ball milling process were also consolidated using SPS under identical conditions, which were designated as GA and GA+BM, respectively. Results showed a notable difference in relative density (approximately 5%) between the (GA+BM)/FMG and GA/FMG composites. Quantitative analysis revealed that reinforcing particles were more evenly distributed in the GA/FMG composite. The (GA+BM)/FMG composite exhibited a compressive yield strength of 156 MPa, double that of the GA/FMG composite, but with reduced ductility. Fractography indicated that the (GA+BM)/FMG composite was more brittle than its GA/FMG counterpart.https://macs.semnan.ac.ir/article_9635_4b6e10b71f0875796c8e37d2c791232f.pdf